2020
DOI: 10.1007/s10554-020-01956-9
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Validation and application of OCT tissue attenuation index for the detection of neointimal foam cells

Abstract: Neointimal infiltration with foamy macrophages is recognized as an early and important sign of de-novo atherosclerosis after stent implantation (neoatherosclerosis). Recent histopathological studies have proven that automated quantification of signal attenuation using intravascular optical coherence tomography (OCT) imaging allows for sensitive identification of macrophages in native atherosclerotic disease. Whether this is true for neointimal foam cells in the setting of neoatherosclerosis remains unknown. Au… Show more

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Cited by 6 publications
(6 citation statements)
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“…Coronary arteries were then cut by an experienced pathologist according to the standard AHA classification. OCT imaging of the single segments was then performed as previously described ( 15 ): After careful preparation, vessels were wired with a 0.014-inch guidewire over which the OCT catheter (2.7-F, St. Jude Medical, St. Paul, Minnesota) was advanced. An imaging pullback was performed from the distal to the proximal arterial segments while simultaneously flushing the vessel with contrast to improve imaging quality (pullback speed 5 mm/s = 120 frames/s).…”
Section: Methodsmentioning
confidence: 99%
See 1 more Smart Citation
“…Coronary arteries were then cut by an experienced pathologist according to the standard AHA classification. OCT imaging of the single segments was then performed as previously described ( 15 ): After careful preparation, vessels were wired with a 0.014-inch guidewire over which the OCT catheter (2.7-F, St. Jude Medical, St. Paul, Minnesota) was advanced. An imaging pullback was performed from the distal to the proximal arterial segments while simultaneously flushing the vessel with contrast to improve imaging quality (pullback speed 5 mm/s = 120 frames/s).…”
Section: Methodsmentioning
confidence: 99%
“…For intravascular imaging, several groups demonstrated the possibility of automated plaque characterization using semiautomated approaches such as quantification of various optical signal properties (e.g. light attenuation) (12)(13)(14)(15). The feasibility of using deep-learning algorithms for detection and visualization of atherosclerotic plaque components was also demonstrated recently (9,11,(16)(17)(18)(19).…”
Section: Introductionmentioning
confidence: 99%
“…A total of 1148 frames from 92 pullbacks were analyzed. Neointimal tissue was classified using a quadrant-based nominal character scoring system as previously described [19]: clockwise and starting at 12 o'clock, every frame was divided into four quadrants (see Figure 1 A), with the center of the lumen as the dividing point. Each quadrant was then independently classified according to its predominant neointimal appearance into one of four classes: homogenous neointima (uniform light reflection without localized areas of stronger or weaker backscattering properties), heterogenous neointima (consisting of a focal variation of the backscattering pattern, including patterns described as "layered"), neoatherosclerosis (containing neointimal foam cells, fibroatheroma or calcifications) [20,21] or not analyzable (quadrants with uncovered struts or side-branch openings).…”
Section: Neointima Classificationmentioning
confidence: 99%
“…However, surrogate measurements such as lipid angle have been validated to better estimate lipid plaque area [ 15 ]. Adventitia is also difficult to observe due to the insufficient penetration and obstruction by the struts from implanted stents [ 16 ]. It is also difficult to determine the boundary of calcification which is near the adventitia.…”
Section: Differences Between Pathology and Intravascular Imaging Of Namentioning
confidence: 99%